ClariLayer is a context layer that connects with any AI you use day to day, so you have durable context about you data, metrics, analysis, etc. The context is durable, cross-sessions and cross-tools, so you will never need to re-explain your data.
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Maker
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Hi everyone! This is Kyle, founder of ClariLayer.
I used to work in data-driven companies like Databricks and Cloudflare. I lived the problem of constantly changing metric definition, poorly maintained documentation, countless data schema issues, etc.
So I left Databricks last year to build a product to solve this problem. I already have real users using ClariLayer for:
- Sales Operations in unicorn startup
- Public infrastructure software development
- Data pipeline management on Databricks and Snowflake
- CRM context management
and so on!
It is completely free for individuals. Under 5 minutes, you can connect it to your AI over MCP, bootstrap context from your existing projects, and start feeling the benefits it brings to your next AI session!
Keen to hear more feedback from the community here!
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@kylehui The idea of persistent AI context is really interesting. How does ClariLayer handle conflicting or outdated context when your data changes over time
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Maker
@dipanshu_kushwaha5 Great question. If two definitions disagree, ClariLayer keeps the conflict visible, including where each definition came from, so the agent doesn’t quietly pick one and move on.
When the underlying source changes, the agent can reconcile a saved definition against fresh warehouse or HubSpot evidence. If they no longer line up, it gets a caveat. Once corrected, the new version supersedes the old one, so the history stays intact.
One honest limitation today: reconciliation is explicit, triggered by you or the agent during a task. ClariLayer isn’t continuously watching the source in the background yet.
@kylehui The idea of persistent AI context is really interesting. How does ClariLayer handle conflicting or outdated context when your data changes over time
@dipanshu_kushwaha5 Great question. If two definitions disagree, ClariLayer keeps the conflict visible, including where each definition came from, so the agent doesn’t quietly pick one and move on.
When the underlying source changes, the agent can reconcile a saved definition against fresh warehouse or HubSpot evidence. If they no longer line up, it gets a caveat. Once corrected, the new version supersedes the old one, so the history stays intact.
One honest limitation today: reconciliation is explicit, triggered by you or the agent during a task. ClariLayer isn’t continuously watching the source in the background yet.